The "Accepting Bad Things" Axiom
In his interview with POLITICO, OpenAI CEO Sam Altman articulated a core philosophy of technology deployment: that historical industrial and digital revolutions inevitably generate unintended adverse externalities, and that seeking zero harm before rollout risks precluding immense humanitarian, medical, and productivity dividends.
This workbench formalizes that argument into quantifiable economic and risk parameters. It models where the boundary lies between acceptable frictional disruption (e.g., transitional labor displacement, moderate synthesis errors) and unacceptable systemic tail risks (e.g., biological weapon synthesis, automated critical infrastructure sabotage).
Pareto Frontier & Analytical Formulation
The Pareto Frontier identifies the envelope where societal benefit cannot be enhanced without either increasing risk exposure or spending additional defensive compute.
- Gross Benefit: $B(v) = \sum B_i \cdot v^{\beta}$, where $v$ is velocity and $\beta \approx 0.85$ represents diminishing marginal returns.
- Externalized Harm: $H(v, m) = \sum R_i \cdot v^{1.25} \cdot (1 - \eta_i(m))$, where $\eta_i$ is mitigation efficacy.
- Tail Risk Multiplier: Applies super-linear penalties ($\gamma$) when critical sectors (Biosecurity, Autonomous Cyber) exceed safety thresholds.
Use this tool to pressure-test regulatory thresholds, compute capital trade-offs, and brief policy stakeholders with verified numerical baselines.